Intro Analytics Modeling - ISYE-6501 Homework 10

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Intro Analytics Modeling - ISYE-6501 Homework 10 Question 14.1 The breast cancer data set breast-cancer-wisconsin.data.txt. 1. Use the mean/mode imputation method to impute values for the missing ... data. 2. Use regression to impute values for the missing data. 3. Use regression with perturbation to impute values for the missing data 4. (Optional) Compare the results and quality of classification models (e.g., SVM, KNN) build using (1) the data sets from questions 1,2,3; (2) the data that remains after data points with missing values are removed; and (3) the data set when a binary variable is introduced to indicate missing values. Answers (R code and results ): 1-3 Examine the data Intro Analytics Modeling - ISYE-6501 Results: Intro Analytics Modeling - ISYE-6501 Imputation using the 3 methods: Intro Analytics Modeling - ISYE-6501 Results: Intro Analytics Modeling - ISYE-6501 4. R code Intro Analytics Modeling - ISYE-6501 Intro Analytics Modeling - ISYE-6501 Results Plots (the 4 models and the error plots) Intro Analytics Modeling - ISYE-6501 Intro Analytics Modeling - ISYE-6501 Intro Analytics Modeling - ISYE-6501 Question 15.1 Describe a situation or problem from your job, everyday life, current events, etc., for which optimization would be appropriate. What data would you need? Answer: Bond Portfolio Management: Allocate funds to bonds to maximize return while ensuring that the portfolio duration equals the investment horizon for maturity - with known or computed durations. Data needed: bond price/bond risk/bond duration/bond maturity/investment horizon [Show More]

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